Rate adaptation

ABSTRACT

This specification describes an apparatus relating to rate adaptation. The apparatus may comprise a processor and a memory including instructions, the instructions, when executed by the processor, cause the apparatus to provide first data representing an estimate of a communications link based on a signal received over said communications link from a transmitter. The apparatus may determine an estimated achievable data rate over said communications link for each of a plurality of link configurations which have respective combinations of modulation scheme and pilot symbol pattern which correspond to one or more transmitter link configurations, the estimated achievable data rate for a particular link configuration being determined based on the first data, and the modulation scheme and the pilot pattern of the particular reference link configuration. The apparatus may select a transmitter link configuration based on the estimated achievable data rates.

FIELD

The present specification relates to an apparatus and method for rateadaptation.

BACKGROUND

In communications, rate adaptation generally comprises a receivingsystem causing a transmitting system to adapt how data is transmitted tothe receiving system (or possibly another receiving system) over acommunications link, for example based on link conditions, in order toachieve a particular data throughput with low error rate.

SUMMARY

The scope of protection sought for various aspects of the invention isset out by the independent claims. The aspects and features, if any,described in this specification that do not fall under the scope of theindependent claims are to be interpreted as examples useful forunderstanding the various aspects of the invention.

According to a first aspect, this specification describes an apparatus,comprising: a processor; and a memory including instructions, theinstructions, when executed by the processor, cause the apparatus to:provide first data representing an estimate of a communications linkbased on a signal received over said communications link from atransmitter; determine an estimated achievable data rate over saidcommunications link for each of a plurality of link configurations whichhave respective combinations of modulation scheme and pilot symbolpattern which correspond to one or more transmitter link configurations,the estimated achievable data rate for a particular link configurationbeing determined based on the first data, and the modulation scheme andthe pilot pattern of the particular reference link configuration; andselect a transmitter link configuration based on the estimatedachievable data rates.

The first data may represent a plurality of complex coefficientsrespectively representing individual link estimates for a plurality ofresource elements comprising all or a majority of the resource elementsof a resource grid of the received signal.

The estimated achievable data rate for each of the link configurationsmay be computed using a computational model which receives the firstdata as input.

The computational model may be trained based on a training datasetcomprising, for each link configuration, (i) first training datarepresenting one or more link estimates and, (ii) second training datarepresenting an achievable data rate for the one or more link estimatesof each link configuration.

One or more of the first and second training data may be provided usingmeasured and/or simulated data.

The first training data may comprise a plurality of complex coefficientsrespectively representing individual link estimates for a plurality ofresource elements comprising all or a majority of the resource elementsof a resource grid

The second training data may be provided by calculating mathematicallyan estimate of a true achievable data rate for a given batch of thefirst training data for each link configuration.

The estimate of the true achievable data rate may be calculatedmathematically based on bit-wise mutual information and using anexpression which depends only on the modulation scheme and pilot symbolpattern of the particular link configuration.

The computational model may be trained by iteratively updatingparameters using a stochastic descent algorithm.

The estimated achievable data rates may be determined in units of bitsper physical resource block (bits/PRB).

Each of the transmitter link configurations may have an advertised datarate, and wherein the apparatus is configured to select the linkconfiguration by: filtering the transmitter link configurations toexclude those having an advertised data rate greater than the estimatedachievable data rate for the corresponding link configuration; andselecting one of the remaining link configurations.

The selected transmitter link configuration may be that having thehighest advertised data rate.

Prior to filtering, the advertised data rate for each of the transmitterlink configurations may be reduced by a predetermined parameter ∈.

The first data may represent estimated frequency responsecharacteristics of a communications link based on receipt of amulti-carrier modulated signal.

The multi-carrier modulated signal may be an Orthogonal FrequencyDivision Multiplexing (OFDM) modulated signal.

The first data may represent a plurality of complex coefficients in aphysical resource block of the multi-carrier modulated signal.

The apparatus may be a communications receiver which is furtherconfigured to send an indication of the selected link configuration tothe transmitter.

The apparatus may be the transmitter, the first data being provided by acommunications receiver based on the received signal.

According to a second aspect, this specification describes an apparatus,comprising means for: providing first data representing an estimate of acommunications link based on a signal received over said communicationslink from a transmitter; determining an estimated achievable data rateover said communications link for each of a plurality of linkconfigurations which have respective combinations of modulation schemeand pilot symbol pattern which correspond to one or more transmitterlink configurations, the estimated achievable data rate for a particularlink configuration being determined based on the first data, and themodulation scheme and the pilot pattern of the particular reference linkconfiguration; and selecting a transmitter link configuration based onthe estimated achievable data rates.

The first data may represent a plurality of complex coefficientsrespectively representing individual link estimates for a plurality ofresource elements comprising all or a majority of the resource elementsof a resource grid of the received signal.

The estimated achievable data rate for each of the link configurationsmay be computed using a computational model which receives the firstdata as input.

The computational model may be trained based on a training datasetcomprising, for each link configuration, (i) first training datarepresenting one or more link estimates and, (ii) second training datarepresenting an achievable data rate for the one or more link estimatesof each link configuration.

One or more of the first and second training data may be provided usingmeasured and/or simulated data.

The first training data may comprise a plurality of complex coefficientsrespectively representing individual link estimates for a plurality ofresource elements comprising all or a majority of the resource elementsof a resource grid

The second training data may be provided by calculating mathematicallyan estimate of a true achievable data rate for a given batch of thefirst training data for each link configuration.

The estimate of the true achievable data rate may be calculatedmathematically based on bit-wise mutual information and using anexpression which depends only on the modulation scheme and pilot symbolpattern of the particular link configuration.

The computational model may be trained by iteratively updatingparameters using a stochastic descent algorithm.

The estimated achievable data rates may be determined in units of bitsper physical resource block (bits/PRB).

Each of the transmitter link configurations may have an advertised datarate, and wherein the apparatus is configured to select the linkconfiguration by: filtering the transmitter link configurations toexclude those having an advertised data rate greater than the estimatedachievable data rate for the corresponding link configuration; andselecting one of the remaining link configurations.

The selected transmitter link configuration may be that having thehighest advertised data rate.

Prior to filtering, the advertised data rate for each of the transmitterlink configurations may be reduced by a predetermined parameter ∈.

The first data may represent estimated frequency responsecharacteristics of a communications link based on receipt of amulti-carrier modulated signal.

The multi-carrier modulated signal may be an Orthogonal FrequencyDivision Multiplexing (OFDM) modulated signal.

The first data may represent a plurality of complex coefficients in aphysical resource block of the multi-carrier modulated signal.

The apparatus may be a communications receiver which is furtherconfigured to send an indication of the selected link configuration tothe transmitter.

The apparatus may be the transmitter, the first data being provided by acommunications receiver based on the received signal.

According to a third aspect, this specification describes a methodcomprising: providing first data representing an estimate of acommunications link based on a signal received over said communicationslink from a transmitter; determining an estimated achievable data rateover said communications link for each of a plurality of linkconfigurations which have respective combinations of modulation schemeand pilot symbol pattern which correspond to one or more transmitterlink configurations, the estimated achievable data rate for a particularlink configuration being determined based on the first data, and themodulation scheme and the pilot pattern of the particular reference linkconfiguration; and selecting a transmitter link configuration based onthe estimated achievable data rates.

According to a fourth aspect, this specification describes a computerprogram comprising a set of instructions which, when executed on anapparatus, is configured to: provide first data representing an estimateof a communications link based on a signal received over saidcommunications link from a transmitter; determine an estimatedachievable data rate over said communications link for each of aplurality of link configurations which have respective combinations ofmodulation scheme and pilot symbol pattern which correspond to one ormore transmitter link configurations, the estimated achievable data ratefor a particular link configuration being determined based on the firstdata, and the modulation scheme and the pilot pattern of the particularreference link configuration; and select a transmitter linkconfiguration based on the estimated achievable data rates.

BRIEF DESCRIPTION OF THE FIGURES

Examples will now be described, by way of example only, with referenceto the accompanying drawings in which:

FIG. 1 is a block diagram of a system according to an exampleembodiment;

FIG. 2 is a schematic view of a time and frequency resource grid;

FIG. 3 is a tabular representation of a data structure indicatingdifferent transmitter link configurations according to an exampleembodiment;

FIG. 4 is a block diagram of a rate estimation module according to anexample embodiment;

FIG. 5 is a tabular representation of a data structure indicatingdifferent reference link configurations according to an exampleembodiment;

FIG. 6A is a schematic view of a neural network for providing acomputational model according to an example embodiment;

FIG. 6B is a schematic view of part of the FIG. 6A neural network;

FIG. 7 is a flow diagram indicating operations for training acomputational model according to an example embodiment;

FIG. 8 is a block diagram of a configuration selection module accordingto an example embodiment;

FIG. 9 is a flow diagram indicating operations for selecting a linkconfiguration according to an example embodiment;

FIG. 10 is a tabular representation of a data structure which may beuseful for understanding the operation of the FIG. 8 configurationselection module;

FIG. 11 is a flow diagram indicating operations according to an exampleembodiment;

FIG. 12 is a graph indicating simulation results over a first rangetype;

FIG. 13 is a graph indicating simulation results over a second rangetype;

FIG. 14A is a graphical representation of a first pilot pattern used insimulations;

FIG. 14B is a graphical representation of a second pilot pattern used insimulations;

FIG. 15 is a block diagram of an apparatus according to an exampleembodiment; and

FIG. 16 is a representative view of a non-transitory medium for storingcomputer-readable code which, when executed by one or more processors orcontrollers, may perform operations according to an example embodiment.

DETAILED DESCRIPTION

In the description and drawings, like reference numerals refer to likeelements throughout.

Example aspects relate to rate adaptation, and particularly to anapparatus, method and/or computer program product for performingoperations at a receiving means, for determining and sending to atransmitting means an indication of how to adapt a current transmitterlink configuration to use a different one of a plurality of other linkconfigurations usable by the transmitting means. In an alternativeembodiment, the operations may be performed at a transmitting means.

Example aspects focus on transmitting and receiving means configured forrespectively encoding and decoding data using Orthogonal FrequencyDivision Multiplexing (OFDM). However, embodiments herein may also beused with other encoding and decoding schemes in which the transmittingmeans may adapt how data is transmitted based on selection of one of aplurality of predetermined transmitter link configurations (i.e. usableby the transmitting means), and consequently may adapt the datathroughput for the link whilst ensuring a relatively low and thereforeappropriate error rate.

As used herein, a communications link may refer to a communicationschannel, which may be a wired or wireless communications channel.

As used herein, a transmitting means (“transmitter”) and receiving means(“receiver”) may refer to any type of transmitting and receivingapparatus or system involved in communications using suchabove-mentioned encoding and decoding schemes. For example, OFDM iscommonly used for mobile communications (e.g. Long Term Evolution (LTE),Fourth Generation (4G) and Fifth Generation (5G) mobile communications),for example in the downlink from a base station to one or more mobileterminals, and also in fields such as internet communications, powerline networks, digital audio broadcasting (DAB) and so on.

As used herein, “providing” may mean “receiving”, “generating” or“determining”.

FIG. 1 is a block diagram of an example system according to some exampleaspects, the system comprised of a transmitter 100 and a receiver 102connected by a communications link 104. As will be appreciated, the link104 may encounter noise or interference 106 which is represented in theFigure, this having the effect of degrading to some extent a frequencyresponse of a modulated signal transmitted by the transmitter 100. Thelink 104 may comprise a wired or wireless link. It will be assumedherein that the link 104 is wireless and therefore “over-the-air”.

The transmitter 100 and receiver 102 may be configured to respectivelyencode and decode data using OFDM. OFDM is one of a broader class ofmulticarrier modulation schemes in which data is carried over multiple,lower rate sub-carriers. OFDM may offers advantages in terms ofrobustness against the indicated noise/interference 106. In overview,OFDM involves mapping data to symbols, each symbol indicated by acomplex number representing an amplitude and phase, with the symbolsbeing divided, in the time domain, into a plurality of parallel slots,and in the frequency domain, into a plurality of N sub-carriers. Thefrequencies of the N sub-carriers are selected so that they are mutuallyorthogonal over one symbol period which permits recovery of each symbolstream independently of the others with reduced risk of inter symbolinterference (ISI).

FIG. 2 is a schematic view of a time and frequency grid 118, or resourcegrid, which may be useful for understanding example aspects. Theabove-mentioned symbols may be considered allocated to a particular partof the resource grid 118, referred to as a resource element 202.Multiple resource elements 202 may be grouped into a resource blockwhich may be considered the smallest unit of resources that can beallocated to a user. Resource blocks may be referred to as physicalresource blocks (PRBs) given that they relate to the physical layer.

Within the resource grid 118 may be allocated so-called pilot symbols. Apilot symbol comprises a form of reference signal which may be used forso-called link estimation. Link estimation refers to an estimation ofthe link's frequency response. Pilot symbols are mapped to knownlocations within the resource grid 118 and the receiver 102 can extractthe reference signals from the locations of the pilot symbols toestimate the link frequency response, usually using a least squares (LS)estimate approach.

Referring back to FIG. 1 , the transmitter wo comprises a modulationmodule no which modulates data according to what may be considered aresource grid representing a plurality of sub-frames of the data.

The modulation module 110 is configured to use one of a set of so-calledtransmitter link configurations

, each one of the set having a respective combination of parameters,including (i) a particular modulation scheme

, (ii) a particular pilot symbol pattern P and (iii) a particular coderate U. The transmitter link configurations

(i.e. those usable by the transmitter 100) in said set are hereinreferred to as “usable link configurations” and may be defined in astandard. In FIG. 1 , access to some form of data structure, referred toas a usable configurations (UC) table, indicative of the usable linkconfigurations

for that transmitter 100 is indicated in FIG. 1 by reference numeral112. The UC table 112 may comprise, for example, a data structurecomprising at least some information from what is commonly referred toas a Modulation and Coding Scheme (MCS) table and additional informationin the form of different pilot patterns which may be determined as partof a particular standard. The UC table 112 may be provided in anysuitable form or format and may even be external to the transmitter woand accessed via a network.

An example of a particular UC table 300 is shown in FIG. 3 . Each usablelink configuration

is given a simple value or index in a first column 301, for convenientreference herein.

A second column 302 of the UC table 300 indicates a particularmodulation scheme

. The available modulation schemes M may, for example, comprisequadrature phase-shift keying (QPSK) or quadrature amplitude modulation(QAM) with different modulation orders available, such as 16, 64 and256. Higher modulation orders may enable higher throughput, but at thecost of lower robustness to noisy links. Other modulation schemes mayalso be used, depending on the standard.

A third column 303 of the UC table 300 indicates a particular pilotpattern P. The available pilot patterns P may be pre-defined in astandard, e.g., comb-type with specific spacings in the frequency andtime domain.

A fourth column 304 of the UC table 300 indicates a particular code rateU. The available code rates U may take values in the range (0,1) andcontrol the amount of redundancy introduced to recover from errors. Ahigher code rate U leads to higher useful throughput, because lessredundancy is introduced, but at the cost of lower resilience to errors.Only a finite set of code rates are generally available in thestandards.

It will be seen that the first and second configurations have identicalvalues of modulation scheme

and pilot pattern P and different values of code rate U.

We may denote by

={m₁, . . . , m_(M)} the set of M modulations schemes available.Similarly, we may denote by

={p₁, . . . , p_(P)} the set of P pilot patterns available and by

={u₁, . . . , u_(U)} the set of U code rates available for modulationand transmission by the modulation module no of the transmitter 100.

Collectively, the set of usable link configurations

may comprise tuples c=(m_(i),u_(j),p_(k)) such that m_(i) ∈

, u_(j)∈

and p_(k)∈

. Not all combinations of modulation schemes, pilot patterns and coderates need to be in

, as some combinations may not be handled by the transmitter/receiver100, 102 or may not be included in the standard.

Each usable link configuration c=(m_(i),u_(j),p_(k))∈

may be associated with a advertised data rate r(c), which may beexpressed in bits per physical resource block (bits/PRB) and which isthe product of three elements:

-   -   the number of bits per channel used that can be transmitted with        the modulation scheme m_(i), e.g., 2 with QPSK, 4 with 16QAM        etc.;    -   the code rate u_(j), e.g., ½, ¾ . . . ; and    -   the number of resource elements carrying data symbols in a PRB        using the pilot pattern p_(k).

As shown in FIG. 3 , a fifth column 305 of the UC table 300 indicates arespective advertised data rate r(c) associated with each usable linkconfiguration c.

The data rate r(c) may be considered “advertised” in that it ispredefined in the particular standard UC table 300 as indicative of anachievable data rate with low error.

Example aspects may relate to selecting a particular configuration cfrom the set of usable configurations

with a data rate r(c) that achieves improved throughput whilstmaintaining a low probability of error, given the current channel state.

Referring back to FIG. 1 , at the receiver 102, demodulation isperformed (OFDM demodulation in this example) to derive a receivedresource grid 119 which may form the basis of link estimation 120. As isknown, the received resource grid 119 may also be used for equalization122 to produce a frequency-domain equalized received resource grid 122from which the original data can be obtained.

A link estimation module 120 may be used to estimate the frequencyresponse of the link 104 using conventional techniques. This may bereferred to as link estimation and, in some example aspects, linkestimation is performed for all, or the majority of resource elements202 of a received resource grid 119 (according to how the resource gridis defined in the relevant communications standard). The receivedresource grid 119 may, for example, comprise a physical resource block(PRB) in OFDM. Link estimation may be performed for resource elements202 associated with locations of pilot symbols, as well as otherresource elements which may carry no data or non-pilot data.

The link estimate provided by the link estimation module 120 maytherefore comprise data representing a matrix of complex numbers orcoefficients, corresponding to all or the majority of resource elements202 of the received resource grid 119, having time slots andsub-carriers as first and second dimensions or a three-dimensionaltensor having as a third dimension real and imaginary components of linkcoefficient estimates. The coefficients of the received resource grid119 may be considered as respective individual estimates of differentlink realizations for each resource element 202.

As noted above, link estimation may be performed based on the knownpattern (locations) of pilot symbols for a current link configuration cwithin the received resource grid 119 using a LS estimate or similarcalculation.

Link estimation in respect of the pilot symbol resource elements maytherefore involve first extracting the pilot symbols from their knownlocations within a received sub-frame and, because their locations areknown, the channel frequency response at these locations can bedetermined using an LS estimate. The LS estimate may be obtained bydividing the received pilot symbols by their expected value. This may bederived from:Y=H·X+Noise  (1)where Y is a received symbol value, X is a transmitted symbol value andH is the complex link gain experienced by a symbol, and may comprise thechannel estimate. The notations Y, X and H are shown in FIG. 1 forconvenience.

For non-pilot resource elements, the same process may also be performedusing, for example, linear minimum mean square error (LMMSE) channelestimation or Wiener filtering or simple linear interpolation.Data-aided channel estimation could also be used.

In example aspects, rate adaptation may therefore be performed based onthe received channel estimate H for the entire, or a major proportionof, the received resource grid 119.

More specifically, the received channel estimate H may be used firstlyto estimate, for each of a plurality of so-called reference linkconfigurations

, having respective combinations of modulation scheme

and pilot symbol pattern

, an estimated achievable data rate {circumflex over (R)} over thecommunications link 104.

Rate Estimation Module 124

As shown in FIG. 1 , and in more detail with reference to FIG. 4 , arate estimation module 124 may be provided for this purpose, which maytake as input a dataset representing the channel estimate H and whichmay generate as output a set of estimated achievable data rates{circumflex over (R)}({tilde over (c)}1) . . . {circumflex over(R)}({tilde over (c)}N) for each of the respective reference linkconfigurations

.

Referring to FIG. 5 , an example set of reference link configurations

are shown in the form of a reference configurations (RC) table 500. TheRC table 500 may be stored at the receiver 102 or is at least accessibleto the receiver. The reference link configurations

in the RC table 500 may correspond to one or more of the usable linkconfigurations

referred to above in relation to the UC table 300, in that they have thesame or similar values of

and

. For reasons that will become clear, the reference link configurations

need not account for different values of code rate

={u₁, . . . , u_(U)} because the estimated achievable data rate is notdependent on the code rate. A first column 501 of the RC table 500represents a simple value or index for convenient reference herein(given as letters “A-D” to distinguish over the UC table 300 shown inFIG. 3 ). A second column 502 indicates modulation schemes

and a third column 503 indicates pilot patterns P. Because code ratesare not needed, the RC table 500 comprises only four entries becauseentry “A” may correspond to both the first and second entries “#1” and“#2” in the UC table 300.

The rate estimation module 124 may comprise a computational model 400,for example a neural network, trained based on one or more datasets forgenerating the above-mentioned estimated achievable data rates{circumflex over (R)}({tilde over (c)}1) . . . R({tilde over (c)}N) forthe respective reference link configurations

, as will be explained below.

The computational model 400 may comprise any known form of trainablemodel which may, for example, be initialized in terms of its parameters(or weights) with random or specific values. The computational model 400may then be trained based on a training dataset, usually using a descentalgorithm such as stochastic gradient descent (SGD), or similar, toreduce or minimize a loss function iteratively until a stop criterion(or criteria) is (or are) reached.

In example aspects, the training dataset may comprise a dataset oftuples ({tilde over (c)}, H, R), where {tilde over (c)} refers to thedifferent combinations of the reference link configurations {tilde over(C)} (i.e. modulation scheme

and pilot pattern

), H refers to channel estimates, and R refers to what may be consideredthe true achievable rate for a given channel estimate H and referencelink configuration {tilde over (c)} combination of the dataset.

At least some values of the training dataset may be obtained usingsimulations or measurements, i.e. simulated or measured data.

The channel estimate H may represent a plurality, e.g. a matrix, ofcomplex coefficients respectively representing a plurality of resourceelements comprising all or a majority of the resource elements of aresource grid, and including resource elements corresponding to pilotsymbols. The matrix may be indicative of multiple time slots andmultiple sub-carriers for representing the one or more estimated linkcharacteristics. The matrix of complex coefficients may represent therespective positions of pilot symbols in a resource block and othernon-pilot symbols, whether non-data or data carrying resource elements.

Data representing the true achievable rate R for a given channelestimate and reference link configuration combination may be determinedmathematically, for example using a given batch of the training datarepresenting a channel estimate H for a particular reference linkconfiguration {tilde over (C)}. An example method for a mathematicaldetermination follows.

Many commercial communication systems rely on bit-interleaved codedmodulation (BICM), for which a known achievable rate is called thebit-wise mutual information (BMI):

$\begin{matrix}{{R_{BMI}:} = {\sum\limits_{i = 1}^{l}{I\left( {b_{i},y} \right)}}} & (2)\end{matrix}$where l is the number of bits per link used, I(.,.) is the mutualinformation, b₁, . . . , b_(l) is the bits transmitted over a link, andy is the corresponding received symbol. The BMI depends on themodulation scheme and pilot pattern used, and therefore on a combination{tilde over (c)}∈

. It is therefore independent of the channel code, and therefore of thecode rate.

However, equation (2) assumes an ideal receiver, i.e. one that performsmaximum likelihood detection (MLD). In practice, MLD cannot be used,especially on realistic links, as it is very complex to implement.

An achievable determination of the true achievable rate R, assuming animperfect receiver, may be provided by:

$\begin{matrix}{{R_{IRX}:} = {R_{BMI} - {\sum\limits_{i = 1}^{l}{{\mathbb{E}}\left\lbrack {D_{KL}\left( {{p\left( b_{i} \middle| y \right)}\left. {\overset{\hat{}}{p}\left( b_{i} \middle| y \right)} \right)} \right\rbrack} \right.}}}} & (3)\end{matrix}$where D_(KL)(·∥·) is the Kullback-Leibler divergence, the expectation isover y, p(b_(i)|y) is the true probability of b_(i) to have beentransmitted given y, and {circumflex over (p)}(b_(i)|y) is theprobability of b_(i) to have been transmitted given y approximated bythe receiver. The second term on the right-hand side accounts for therate loss due to an imperfect receiver.

It is found that the achievable rate R_(IRX) can be re-written using thetotal binary cross-entropy:

$\begin{matrix}{R_{IRX} = {l - {\sum\limits_{i = 1}^{l}{{\mathbb{E}}\left\lbrack {H\left( {{p\left( b_{i} \middle| y \right)},{\overset{\hat{}}{p}\left( b_{i} \middle| y \right)}} \right\rbrack} \right.}}}} & (4)\end{matrix}$where H(.,.) is the cross-entropy, and the second term on the right-handside is the total binary cross-entropy. Therefore, minimizing the totalbinary cross-entropy is equivalent to maximizing the achievable rateconsidering an imperfect receiver.

Therefore, the true achievable rate can be estimated using:

$\begin{matrix}{T = {m + {\frac{1}{B}{\sum\limits_{j = 1}^{B}{\sum\limits_{i = 1}^{l}\left( {{b_{i}^{(j)}\log\left( {\overset{\hat{}}{p}\left( b_{i}^{\{{(j)}\}} \right)} \right)} + {\left( {1 - b_{i}^{(j)}} \right)\log\left( {1 - {\overset{\hat{}}{p}\left( b_{i}^{\{{(j)}\}} \right)}} \right)}} \right)}}}}} & (5)\end{matrix}$where B is the batch size, i.e., the number of samples used to computethe estimation, and (j) refers to the jth batch example. T depends onlyon a combination {tilde over (c)} of modulation scheme and pilot pattern

and the result given in bits per resource element.

To get the achievable rate in bits per PRB, denoted by R, we canmultiply T by the number of data-carrying resource elements in a PRB,which depends on the pilot pattern, i.e.,R=T×#(data carrying resource element in a PRB)  (6)FIGS. 6A and 6B are schematic views of an example architecture fortraining a computational model 400 using the above-mentioned trainingdataset and thereafter using the trained computational model as part ofthe rate estimation module 124 shown in FIGS. 1 and 4. As shown in FIG.6A, a residual convolutional neural network 600 may be used, comprisingan input convolutional layer 601, one or more residual neural network(ResNet) blocks 602, an output convolutional layer 603 and an averagepooling layer 604. FIG. 6B shows in more detail an example knownstructure of a residual neural network block 602.

FIG. 7 is a flow diagram showing processing operations that may beperformed as part of the above-mentioned computational model trainingprocess. The process may comprise fewer or greater operations in someembodiments. The operations may be performed in hardware, software,firmware or a combination thereof.

A first operation 701 may comprise initializing the computational model,e.g. by initializing the weights randomly.

A second operation 702 may comprise sampling B examples from thetraining dataset, e.g.:({tilde over (c)} ^((i)) ,H ^((i)) ,R ^((i))),i=1 . . . B′.

A third operation 703 may comprise computing achievable rate predictions{circumflex over (R)}({tilde over (c)}^((i))) from the channel estimatesH^((i)). [ono] A fourth operation 704 may comprise iteratively updatingthe model (i.e. the parameters or weights) for example based on adescent algorithm, e.g. by performing one step of Stochastic GradientDescent (SGD) on the mean squared error (MSE):

$\begin{matrix}{{{MSE} = \left. {\frac{1}{B^{\prime}}\sum\limits_{i = 1}^{B^{\prime}}} \middle| {{\overset{\hat{}}{R}\left( {\overset{˜}{c}}^{(i)} \right)} - R^{(i)}} \right.}❘}^{2} & (7)\end{matrix}$

A fifth operation 705 may comprise determining if a stop criterion ismet. If yes, a sixth operation 706 may comprise stopping the trainingprocess. If not, the process may return to the second operation 702.

The stop criterion in the fifth operation 705 may comprise differentmethods. For example, the training may stop after a predetermined numberof iterations or when the loss function used in SGD has not decreasedfor a predetermined number of iterations. In some example aspects, hyperparameters such as learning rate, batch size, and possibly otherparameters of a SGD variant, may comprise optimization hyper parameters.

As an alternative to using a trained computational model 400, so-calledMonte Carlo methods may be used based on the link estimate H. Forexample, link outputs could be simulated based on randomly sampled linkinputs and noise models, assuming the link estimate H is the true linkresponse. The use of a trained computational model 400 is, however,found to be computationally less expensive.

Configuration Selection Module 126

Referring to FIGS. 1 and 8 , a configuration selection module 126 isprovided for performing selection of a particular one of the usable linkconfigurations

referred to in the UC table 300 of FIG. 3 for achieving an improved datathroughput whilst maintaining a low error rate.

The configuration selection module 126 may receive as input the set ofestimated achievable data rates {circumflex over (R)}({tilde over (c)}1). . . {circumflex over (R)}({tilde over (c)}N) from the rate estimationmodule 124. These estimated achievable data rates {circumflex over(R)}({tilde over (c)}1) . . . {circumflex over (R)}({tilde over (c)}N)for the different combinations of reference link configurations {tildeover (c)}∈

can be extended to the usable link configurations c∈

based on corresponding modulation scheme and pilot pattern, because theestimates do not depend on the code rate.

Therefore, given a usable link configuration c=(m_(i),u_(j),p_(k)), wemay define its achievable rate {circumflex over (R)}(c) as:R{circumflex over (()}c):={circumflex over (R)}({tilde over (c)}), where{tilde over (c)}=(m _(i) ,p _(k))  (8)

The configuration selection module 126 may be configured to select aparticular one, referred to herein as “C*”, of the usable linkconfigurations in the UC table 300 of FIG. 3 . The configurationselection module 126 may then send an indication thereof to thetransmitter 100 over a control link 128 for enabling the transmitter 100to adapt the modulation no to the selected link configuration C.

This feedback may be direct or indirect and may be performed over awired or wireless link.

In some example aspects, the configuration selection module 126 mayselect the usable link configuration C* which has the highest advertiseddata rate (c) but which does not exceed the achievable data rate r(c) ofthe corresponding reference link configuration, which would otherwisecause the error rate to increase given that the achievable data rater(c) gives a more accurate representation. This may be performed by theconfiguration selection module 126 first filtering-out, or excluding,those usable data link configurations c for which the advertised datarate is the same, or higher than, the achievable data rate. In otherwords, the configuration selection module 126 may filter the usable datalink configurations c to exclude those having an advertised data rateequal or greater to the estimated achievable rate for the correspondinglink configuration. From the filtered list, a usable data linkconfiguration c is selected, for example the one having the highestvalue of r(c) is selected as C* and fed back to the transmitter 100.

This may be expressed as:

$\begin{matrix}{c^{*} = {\arg{\max\limits_{c \in C}\left\{ {r(c)} \middle| {{r(c)} < {\overset{\hat{}}{R}(c)}} \right\}}}} & (9)\end{matrix}$

In this way, the usable link configuration C* having the highestthroughput is chosen in such a way that its data rate will achieve lowprobability of error.

In some example aspects, equation (9) may be modified to include theparameter ∈. As practical forward error correction (FEC) codes do notenable arbitrarily small error rates, even when operating at rates belowthe achievable rate, this non-negative parameter E servers to safeguardagainst high error rates, and can be used to control a tradeoff betweenhigh throughput and the desired error rate. Typically, a small value ofE is sufficient, e.g. 0.1 bits per resource element and so, similar toequation (6), the value 0.1 may be multiplied by the number ofdata-carrying resource elements.

Equation (9) may therefore be modified to:

$\begin{matrix}{c^{*} = {\arg\max\limits_{c \in C}\left\{ {r(c)} \middle| {{r(c)} < {{\overset{\hat{}}{R}(c)} - \epsilon}} \right\}}} & (10)\end{matrix}$

FIG. 9 is a flow diagram showing processing operations that may beperformed as part of the above-mentioned selection process. The processmay comprise fewer or greater operations in some embodiments. Theoperations may be performed in hardware, software, firmware or acombination thereof.

A first operation 901 may comprise receiving the estimated achievabledata rates.

A second operation 902 may comprise selecting the usable linkconfiguration with the highest advertised data rate which does notexceed the estimated data rate of the corresponding reference linkconfiguration.

A third operation 903 may comprise sending an indication of the selectedusable link configuration to the transmitter 100.

FIG. 10 is a tabular visualization 950 of a data structure which may beuseful for understanding the operation of the of configuration selectionmodule 126. The first five columns 951-955 correspond to the first fivecolumns 301-305 of FIG. 3 , representing the UC table 300. The sixthcolumn 956 indicates the estimated achievable rates R(c) given in bitsper PRB, as indicated above, for comparison with the fifth column 955.It will be seen from box 960 that the same value of {circumflex over(R)}(c1) can be used for the first two usable link configurationsbecause the different data rates are irrelevant. As an example, if thevalues in the fifth column 955 for r₃, r₄ and r₅ exceed the respectivevalues of {circumflex over (R)}(c2), {circumflex over (R)}(c3) and{circumflex over (R)}(c4), then usable link configurations #3, #4 and #5are excluded from selection. Then, one of the configurations #1 and #2is selected which has the highest data rate r(c) in the fifth column.

FIG. 11 is a flow diagram showing processing operations that may beperformed according to example aspects. The process may comprise feweror greater operations in some aspects. The operations may be performedin hardware, software, firmware or a combination thereof.

A first operation 1101 may comprise providing first data representing anestimate of a communications link based on a signal received over saidcommunications link from a transmitter.

A second operation 1102 may comprise determining an estimated achievabledata rate over said communications link for each of a plurality of linkconfigurations which have respective combinations of modulation schemeand pilot symbol pattern which correspond to one or more transmitterlink configurations, the estimated achievable data rate for a particularlink configuration being determined based on the first data, and themodulation scheme and the pilot pattern of the particular reference linkconfiguration.

A third operation 1103 may comprise selecting a transmitter linkconfiguration based on the respective estimated achievable data rates.

A fourth operation 1104 may comprise sending an indication of theselected link configuration to the transmitter.

At the transmitter, if the indicated selected link configuration isdifferent from that currently used, the selected link configuration maybe used in place of the current one (i.e. it is adapted).

Advantages of example aspects include enabling transmitter adaptation inan improved way by taking into account multiple link characteristics orfeatures, including respective combinations of modulation scheme andpilot pattern. Example aspects may therefore be more accurate andbeneficial in terms of throughput than adaptation methods that are basedonly on, for example, a channel quality indicator (CQI) which is ascalar value based on an estimate of signal-to-noise ratio (SNR). Also,if the computational model receives channel estimates for the entire, ora substantial part of the received resource grid, instead of using asingle scalar such as average SNR, it is possible to predict how timeand spatial correlations impact the rate, given a sub-optimal receiver.This enables a more accurate estimate of the achievable rate as itaccounts for Doppler and delay spread.

Accuracy is furthermore enabled by determining estimated achievable datarates for reference link configurations using assumptions on non-idealreceivers and, for example, using bit-wise mutual information (BMI).

Further advantages may result from the use of a computational model fordetermining the estimated achievable data rates, whereby, for an uplink,the computational model can be trained at a communications cell basestation or some other node, e.g. in a core network, for one or moreparticular transmitters, e.g. all user terminals associated with thebase station. The model may thereafter be deployed to the base stationwhich serves as the receiver in this situation. For a downlink, thecomputational model may be trained for a specific receiver, e.g. a userterminal or type of user terminal, e.g. different computational modelsmay be trained for user terminals provided by different manufacturers.Training may be performed offline and/or remote from user terminalsgiven their limited processing capabilities and the terminals updatedwith the trained computational model.

The computational model, during training, may adapt to the particularlink conditions of a given receiver or receivers in a particular cell.

Specific Examples of Technical Purpose

Example aspects may comprise use of the rate estimation andconfiguration selection methods and modules 124, 126 described hereinfor one or more technical purposes. For example, the methods and modules124, 126 may be provided as part of a communications receiver, e.g. at acellular communications base station and/or mobile terminal, among otherexamples.

Evaluation

FIGS. 12 and 13 provide simulation results which may be useful forunderstanding advantages of example aspects. FIG. 12 shows estimated andtrue achievable data rates over a SNR range in dBs whereas FIG. 13 showsestimated and true achievable data rates over a speed range in km/h.

The estimated achievable data rates, determined by the rate estimationmodule 124, were evaluated using a channel model comprising (merely byway of example) a Jakes Doppler power spectrum and a 3GPP tapped delayline (TDL-A) power delay profile.

A computational model for estimating achievable data rates was trainedfor QPSK and 16QAM modulation schemes, and for two pilot patterns fromthe 5G New Radio (NR) standard, resulting in 4 possible combinations.The computational model, a Neural Network, was trained as describedabove for signal-to-noise SNRs ranging from −10 to 25 dB and for speedsranging from 0 to 125 km/h.

In these simulations, the computational model received as input achannel matrix of dimension 1 transmission timing interval (TTI) with 14time slots and 72 subcarriers, corresponding to 6 physical resourceblocks (PRBs).

As shown in FIGS. 12 and 13 , the computational model was ableaccurately to estimate the achievable data rates, in bits per PRB, whenthe SNR and the speed variate. The two pilot patterns are indicated inFIGS. 12 and 13 as 1P and 2P and graphical representations respectivelyshown in FIGS. 14A and 15B

In the above description, the link estimation module 120 and theconfiguration selection module 126 are provided at the receiver 102 sothat an indication of selected link configuration is sent to thetransmitter 100. In an alternative embodiment, the link estimationmodule 120 and the configuration selection module 126 may be provided atthe transmitter 100. The transmitter 100 may receive the link estimationH from the receiver 102, possibly in compressed form, and otherwise mayperform the same or similar operations to those described above.

Hardware

For completeness, FIG. 15 is an example schematic diagram of componentsof one or more of the apparatuses or modules thereof described above.FIG. 15 shows an apparatus according to an embodiment. The apparatus maybe configured to perform the operations described herein, for exampleoperations described with reference to FIGS. 7, 9 and/or 11 . Theapparatus comprises at least one processor 1400 and at least one memory1410 directly or closely connected to the processor. The memory 1410includes at least one random access memory (RAM) 1410 b and at least oneread-only memory (ROM) 1410 a. Computer program code (software) 1430 isstored in the ROM 1410 a. The at least one processor 1400, with the atleast one memory 1410 and the computer program code 1430 are arranged tocause the apparatus to at least perform at least the method according toFIGS. 7, 9 and/or 11 .

FIG. 16 shows a non-transitory media 1500 according to some embodiments.The non-transitory media 1500 is a computer readable storage medium. Itmay be e.g. a CD, a DVD, a USB stick, a blue ray disk, etc. Thenon-transitory media 1500 stores computer program code causing anapparatus to perform the method of FIGS. 7, 9 and/or 11 .

The processing apparatus of FIG. 15 may be at least part of a standalonecomputer, a server, a console, an apparatus, a user device, a mobilecommunication device, an IoT device, a sensor, a software application, acommunication network, or any combination thereof. In some exampleembodiments, the processing apparatus may also be associated withexternal software applications. These may be applications stored on aremote server device and may run partly or exclusively on the remoteserver device. These applications may be termed cloud-hostedapplications. The processing apparatus may be in communication with theremote server device in order to utilize the software application storedthere.

Some example embodiments of the present invention may be implemented insoftware, hardware, application logic or a combination of software,hardware and application logic. The software, application logic and/orhardware may reside on memory, or any computer media. In an exampleembodiment, the application logic, software or an instruction set ismaintained on any one of various conventional computer-readable media.In the context of this document, a “memory” or “computer-readablemedium” may be any non-transitory media or means that can contain,store, communicate, propagate or transport the instructions for use byor in connection with an instruction execution system, apparatus, ordevice, such as a computer.

Reference to, where relevant, “computer-readable storage medium”,“computer program product”, “tangibly embodied computer program” etc.,or a “processor” or “processing circuitry” etc. should be understood toencompass not only computers having differing architectures such assingle/multi-processor architectures and sequencers/parallelarchitectures, but also specialized circuits such as field programmablegate arrays FPGA, application specify circuits ASIC, signal processingdevices and other devices. References to computer program, instructions,code etc. should be understood to express software for a programmableprocessor firmware such as the programmable content of a hardware deviceas instructions for a processor or configured or configuration settingsfor a fixed function device, gate array, programmable logic device, etc.

As used in this application, the term “circuitry” may refer to one ormore or all of the following:

-   -   (a) hardware-only circuit implementations (such as        implementations in only analog and/or digital circuitry) and    -   (b) combinations of hardware circuits and software, such as (as        applicable):        -   (i) a combination of analog and/or digital hardware            circuit(s) with software/firmware and        -   (ii) any portions of hardware processor(s) with software            (including digital signal processor(s)), software, and            memory(ies) that work together to cause an apparatus, such            as a mobile phone or server, to perform various functions),            and    -   (c) hardware circuit(s) and or processor(s), such as a        microprocessor(s) or a portion of a microprocessor(s), that        requires software (e.g., firmware) for operation, but the        software may not be present when it is not needed for        operation.”

This definition of circuitry applies to all uses of this term in thisapplication, including in any claims. As a further example, as used inthis application, the term circuitry also covers an implementation ofmerely a hardware circuit or processor (or multiple processors) orportion of a hardware circuit or processor and its (or their)accompanying software and/or firmware. The term circuitry also covers,for example and if applicable to the particular claim element, abaseband integrated circuit or processor integrated circuit for a mobiledevice or a similar integrated circuit in server, a cellular networkdevice, or other computing or network device.

If desired, the different functions discussed herein may be performed ina different order and/or concurrently with each other. Furthermore, ifdesired, one or more of the above-described functions may be optional ormay be combined. Similarly, it will also be appreciated that the flowdiagrams of FIGS. 7, 9 and 11 are examples only and that variousoperations depicted therein may be omitted, reordered and/or combined.

It will be appreciated that the above described example embodiments arepurely illustrative and are not limiting on the scope of the invention.Other variations and modifications will be apparent to persons skilledin the art upon reading the present specification.

Moreover, the disclosure of the present application should be understoodto include any novel features or any novel combination of featureseither explicitly or implicitly disclosed herein or any generalizationthereof and during the prosecution of the present application or of anyapplication derived therefrom, new claims may be formulated to cover anysuch features and/or combination of such features.

Although various aspects of the invention are set out in the independentclaims, other aspects of the invention comprise other combinations offeatures from the described example embodiments and/or the dependentclaims with the features of the independent claims, and not solely thecombinations explicitly set out in the claims.

It is also noted herein that while the above describes various examples,these descriptions should not be viewed in a limiting sense. Rather,there are several variations and modifications which may be made withoutdeparting from the scope of the present invention as defined in theappended claims.

The invention claimed is:
 1. An apparatus, comprising: a processor; anda memory including instructions, the instructions, when executed by theprocessor, cause the apparatus to: provide first data representing anestimate of a communications link based on a signal received over saidcommunications link from a transmitter; determine an estimatedachievable data rate over said communications link for each of aplurality of link configurations which have respective combinations ofmodulation scheme and pilot symbol pattern which correspond to one ormore transmitter link configurations, the estimated achievable data ratefor a particular link configuration being determined based on the firstdata, and the modulation scheme and the pilot pattern of the particularreference link configuration, and wherein each of the transmitter linkconfigurations has a respective advertised data rate; and select atransmitter link configuration by: filtering the transmitter linkconfigurations to exclude those having an advertised data rate greaterthan the estimated achievable data rate for the corresponding linkconfiguration; and selecting one of the remaining link configurations.2. The apparatus of claim 1, wherein the first data represents aplurality of complex coefficients respectively representing individuallink estimates for a plurality of resource elements comprising all or amajority of the resource elements of a resource grid of the receivedsignal.
 3. The apparatus of claim 1, wherein the estimated achievabledata rate for each of the link configurations is computed using acomputational model which receives the first data as input.
 4. Theapparatus of claim 3, wherein the computational model is trained basedon a training dataset comprising, for each link configuration, (i) firsttraining data representing one or more link estimates and, (ii) secondtraining data representing an achievable data rate for the one or morelink estimates of each link configuration.
 5. The apparatus of claim 4,wherein the first training data comprises a plurality of complexcoefficients respectively representing individual link estimates for aplurality of resource elements comprising all or a majority of theresource elements of a resource grid.
 6. The apparatus of claim 4,wherein the second training data is provided by calculatingmathematically an estimate of a true achievable data rate for a givenbatch of the first training data for each link configuration.
 7. Theapparatus of claim 6, wherein the estimate of the true achievable datarate is calculated mathematically based on bit-wise mutual informationand using an expression which depends only on the modulation scheme andpilot symbol pattern of the particular link configuration.
 8. Theapparatus of claim 1, wherein the estimated achievable data rates aredetermined in units of bits per physical resource block (bits/PRB). 9.The apparatus of claim 1, wherein the selected transmitter linkconfiguration is that having the highest advertised data rate.
 10. Theapparatus of claim 1, wherein, prior to filtering, the advertised datarate for each of the transmitter link configurations is reduced by apredetermined parameter ∈.
 11. The apparatus of claim 1, wherein thefirst data represents estimated frequency response characteristics of acommunications link based on receipt of a multi-carrier modulatedsignal.
 12. A method, comprising: providing first data representing anestimate of a communications link based on a signal received over saidcommunications link from a transmitter; determining an estimatedachievable data rate over said communications link for each of aplurality of link configurations which have respective combinations ofmodulation scheme and pilot symbol pattern which correspond to one ormore transmitter link configurations, the estimated achievable data ratefor a particular link configuration being determined based on the firstdata, and the modulation scheme and the pilot pattern of the particularreference link configuration, and wherein each of the transmitter linkconfigurations has a respective advertised data rate; and selecting atransmitter link configuration by: filtering the transmitter linkconfigurations to exclude those having an advertised data rate greaterthan the estimated achievable data rate for the corresponding linkconfiguration; and selecting one of the remaining link configurations.13. The method of claim 12, wherein the first data represents aplurality of complex coefficients respectively representing individuallink estimates for a plurality of resource elements comprising all or amajority of the resource elements of a resource grid of the receivedsignal.
 14. The method of claim 12, wherein the estimated achievabledata rate for each of the link configurations is computed using acomputational model which receives the first data as input.
 15. Themethod of claim 14, wherein the computational model is trained based ona training dataset comprising, for each link configuration, (i) firsttraining data representing one or more link estimates and, (ii) secondtraining data representing an achievable data rate for the one or morelink estimates of each link configuration.
 16. The method of claim 15,wherein the first training data comprises a plurality of complexcoefficients respectively representing individual link estimates for aplurality of resource elements comprising all or a majority of theresource elements of a resource grid.
 17. The method of claim 15,wherein the second training data is provided by calculatingmathematically an estimate of a true achievable data rate for a givenbatch of the first training data for each link configuration.
 18. Themethod of claim 17, wherein the estimate of the true achievable datarate is calculated mathematically based on bit-wise mutual informationand using an expression which depends only on the modulation scheme andpilot symbol pattern of the particular link configuration.
 19. Themethod of claim 12, wherein the estimated achievable data rates aredetermined in units of bits per physical resource block (bits/PRB). 20.A non-transitory computer-readable medium comprising a computer programwhich, when executed on an apparatus, causes the apparatus to: providefirst data representing an estimate of a communications link based on asignal received over said communications link from a transmitter;determine an estimated achievable data rate over said communicationslink for each of a plurality of link configurations which haverespective combinations of modulation scheme and pilot symbol patternwhich correspond to one or more transmitter link configurations, theestimated achievable data rate for a particular link configuration beingdetermined based on the first data, and the modulation scheme and thepilot pattern of the particular reference link configuration, andwherein each of the transmitter link configurations has a respectiveadvertised data rate; and select a transmitter link configuration by:filtering the transmitter link configurations to exclude those having anadvertised data rate greater than the estimated achievable data rate forthe corresponding link configuration; and selecting one of the remaininglink configurations.